… to the data set to allow it to influence the selected models. … possible to carry out retrospective
tests that verify the consistency of … the models, retrospective tests cannot be used for model …

… in a Bayesian framework two quantities: (1) measure of influence, … No reliable, routinely
available diagnostic test predicts the … parameter model where the HRQoL and survival models …

… Bayesian deep learning model employed in this work only consisted of a single LSTM and
dense layer that limits its nonlinearity modeling … of the parameters that influence the integral. …

… to conduct a prior sensitivity analysis to fully understand the influence that the prior settings
have on … discuss the fluidity of Bayesian model building, inference, diagnostics and model …

… by the explainability model (colour scale indicates the influence on the model prediction). An
… incorporated Cox regression used for survival analysis into DL and trained these models on …

… analysis between Bayes theorem, logistic regression, discrimination analysis, and Bayesian
logit models. … improved after fitting the model with and without the influential factors. The …

… habits of workers exert a considerable influence on the safety … Hence, SPSS was adopted
in this study to conduct the tests. … Both tests confirm the suitability and reliability of variables for …

… The choice of copula function also influences the difference λ 1 ( t ) − λ 1 Sub ( t ) . We do
not … We suggest comparing the two Cox models with aid of graphical diagnostic tools. We …

… construction of a model that shows the influence of the multiple … diagnostic analysis inference
will be used to calculate the posterior probability distribution of each risk factor in the case …

… Overall survival was calculated from time of diagnosis to the last follow… In case of an overall
survival analysis using the Kaplan–… regression (100%), Bayesian network (92%), discriminant …